Luma-based chroma intra-prediction for video coding

ABSTRACT

A method for luma-based chroma intra-prediction in a video encoder or a video decoder is provided that includes filtering reconstructed neighboring samples of a reconstructed down sampled luma block, computing parameters α and β of a linear model using the filtered, reconstructed neighboring samples of the reconstructed down sampled luma block and reconstructed neighboring samples of a corresponding chroma block, wherein the linear model is Pred C [x,y]=α·Rec L ′[x,y]+β, wherein x and y are sample coordinates, Pred C  is predicted chroma samples, and Rec L ′ is samples of the reconstructed down sampled luma block, and computing samples of a predicted chroma block from corresponding samples of the reconstructed down sampled luma block using the linear model and the parameters.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/470,186 field May 11, 2012, which application claims the benefit ofU.S. Provisional Patent Application Ser. No. 61/485,381, filed May 12,2011, both of which are incorporated herein by reference in theirentirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

Embodiments of the present invention generally relate to luma-basedchroma intra-prediction in video coding.

2. Description of the Related Art

Video compression, i.e., video coding, is an essential enabler fordigital video products as it enables the storage and transmission ofdigital video. In general, video compression techniques applyprediction, transformation, quantization, and entropy coding tosequential blocks of pixels in a video sequence to compress, i.e.,encode, the video sequence. Video decompression techniques generallyperform the inverse of these operations in reverse order to decompress,i.e., decode, a compressed video sequence.

The Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T WP3/16and ISO/IEC JTC 1/SC 29/WG 11 is currently developing thenext-generation video coding standard referred to as High EfficiencyVideo Coding (HEVC). HEVC is expected to provide around 50% improvementin coding efficiency over the current standard, H.264/AVC, as well aslarger resolutions and higher frame rates. To address theserequirements, HEVC utilizes larger block sizes than H.264/AVC. In HEVC,the largest coding unit (LCU) can be up to 64×64 in size, while inH.264/AVC, the macroblock size is fixed at 16×16.

Several coding efficiency enhancement tools are proposed in HEVC toreduce coding overhead. One such coding tool is luma-based chromaintra-prediction. In general, in luma-based chroma intra-prediction,chroma values in a block are predicted from down sampled reconstructedluma samples in the same block. More detailed descriptions of thiscoding tool for HEVC may be found, for example, in J. Kim, et al., “NewIntra Chroma Prediction Using Inter-Channel Correlation,” JCTVC-B021,Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 andISO/IEC JTC1/SC29/WG11, Geneva, C H, Jul. 21-28, 2010, J. Chen and V.Seregin, “Chroma Intra Prediction by Reconstructed Luma Samples,”JCTVC-C206, Joint Collaborative Team on Video Coding (JCT-VC) of ITU-TSG16 WP3 and ISO/IEC JTC1/SC29/WG11, Guangzhou, C N, Oct. 7-15, 2010, J.Chen, et al., “CE6.a: Chroma Intra Prediction by Reconstructed LumaSamples,” JCTVC-D350, Joint Collaborative Team on Video Coding (JCT-VC)of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, Daegu, K R, Jan. 20-28,2011, and J. Chen, et al., “CE6.a.4: Chroma Intra Prediction byReconstructed Luma Samples,” JCTVC-E266, Joint Collaborative Team onVideo Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11,Geneva, C H, Mar. 16-23, 2011.

SUMMARY

Embodiments of the present invention relate to methods and apparatus forluma-based chroma intra-prediction in video coding. In one aspect, amethod for luma-based chroma intra-prediction in a video encoder or avideo decoder is provided that includes filtering reconstructedneighboring samples of a reconstructed down sampled luma block,computing parameters α and β of a linear model using the filtered,reconstructed neighboring samples of the reconstructed down sampled lumablock and reconstructed neighboring samples of a corresponding chromablock, wherein the linear model is Pred_(C)[x,y]=α·Rec_(L)′[x,y]+β,wherein x and y are sample coordinates, Pred_(C) is predicted chromasamples, and Rec_(L)′ is samples of the reconstructed down sampled lumablock, and computing samples of a predicted chroma block fromcorresponding samples of the reconstructed down sampled luma block usingthe linear model and the parameters.

In one aspect, a method for luma-based chroma intra-prediction in avideo encoder or a video decoder is provided that includes computingparameters α and β of a linear model using reconstructed neighboringsamples of a reconstructed down sampled luma block and of acorresponding chroma block, wherein the linear model isPred_(C)[x,y]=α·Rec_(L)′[x,y]+β, wherein x and y are sample coordinates,Pred_(C) is predicted chroma samples, and Rec_(L)′ is samples of thereconstructed down sampled luma block;

normalizing the parameter α, and computing samples of a predicted chromablock from corresponding samples of the reconstructed down sampled lumablock using the linear model and the parameters.

In one aspect, a method for luma-based chroma intra-prediction in avideo encoder or a video decoder is provided that includes determining atype of luma-based chroma intra-prediction to be used, wherein the typeis one of a plurality of types of luma-based chroma intra-prediction,and performing luma-based chroma intra-prediction according to thedetermined type to generate a predicted chroma block.

BRIEF DESCRIPTION OF THE DRAWINGS

Particular embodiments will now be described, by way of example only,and with reference to the accompanying drawings:

FIG. 1 illustrates prior art parameter derivation for luma-based chromaintra-prediction;

FIG. 2 is a block diagram of a digital system;

FIG. 3 is a block diagram of a video encoder;

FIG. 4 is a block diagram of a video decoder;

FIGS. 5-11 are flow diagrams of methods; and

FIG. 12 is a block diagram of an illustrative digital system.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

Specific embodiments of the invention will now be described in detailwith reference to the accompanying figures. Like elements in the variousfigures are denoted by like reference numerals for consistency.

As used herein, the term “picture” may refer to a frame or a field of aframe. A frame is a complete image captured during a known timeinterval. For convenience of description, embodiments of the inventionare described herein in reference to HEVC. One of ordinary skill in theart will understand that embodiments of the invention are not limited toHEVC. In HEVC, a largest coding unit (LCU) is the base unit used forblock-based coding. A picture is divided into non-overlapping LCUs. Thatis, an LCU plays a similar role in coding as the macroblock ofH.264/AVC, but it may be larger, e.g., 32×32, 64×64, etc. An LCU may bepartitioned into coding units (CU). A CU is a block of pixels within anLCU and the CUs within an LCU may be of different sizes. Thepartitioning is a recursive quadtree partitioning. The quadtree is splitaccording to various criteria until a leaf is reached, which is referredto as the coding node or coding unit. The maximum hierarchical depth ofthe quadtree is determined by the size of the smallest CU (SCU)permitted. The coding node is the root node of two trees, a predictiontree and a transform tree. A prediction tree specifies the position andsize of prediction units (PU) for a coding unit. A transform treespecifies the position and size of transform units (TU) for a codingunit. A transform unit may not be larger than a coding unit and the sizeof a transform unit may be 4×4, 8×8, 16×16, and 32×32. The sizes of thetransforms units and prediction units for a CU are determined by thevideo encoder during prediction based on minimization of rate/distortioncosts.

Some aspects of this disclosure have been presented to the JCT-VC in M.Budagavi and A. Osamoto, “Luma-Based Chroma Intra PredictionSimplification”, JCTVC-F233, Joint Collaborative Team on Video Coding(JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, Torino, I T, Jul.14-22, 2011, which is incorporated by reference herein in its entirety.

As previously discussed, luma-based chroma intra-prediction is a newcoding tool proposed in HEVC. In general, in luma-based chromaintra-prediction, chroma values for a block of video data are predictedfrom down sampled luma samples of the same block as follows:

Prec_(C) [x,y]=α·Rec_(L) ′[x,y]+β  (1)

where Pred_(C) is the predicted chroma samples and Rec_(L)′ is the downsampled reconstructed luma samples. In essence, the predicted chromasamples are modeled as a linear function of luma samples of the currentluma block. The reconstructed luma samples are down sampled to match thesize and phase of the reconstructed chroma samples. Down sampling, alsoreferred to as sub sampling, is the process of reducing the samplingrate of signal and is usually done to reduce the size of the data. IfRec_(L) is the reconstructed luma samples in a block, Rec_(L)′ iscalculated as follows:

Rec_(L) ′[x,y]=(Rec_(L)[2x,2y]+Rec_(L)[2x,2y+1])>>1.  (2)

Parameters α and β are derived from reconstructed samples neighboringthe current chroma and luma blocks. FIG. 1 shows an example of thelocations of these neighboring samples for an N×N chroma block and a2N×2N luma block. In this figure, the shaded dots illustrate thepositions of the reconstructed neighboring chroma and luma samples,RecN_(C), and RecN_(L), around the respective chroma and luma block.

The ordinary least square (OLS) technique, also referred to as thelinear least squares technique, is used to derive the parameters α andβ:

$\begin{matrix}{\alpha = {\frac{{I{\sum\limits_{i = 0}^{I - 1}{{{RecN}_{C}(i)}{{RecN}_{L}(i)}}}} - {\sum\limits_{i = 0}^{I - 1}{{{RecN}_{C}(i)}\; {\sum\limits_{i = 0}^{I - 1}{{RecN}_{L}(i)}}}}}{{I{\sum\limits_{i = 0}^{I - 1}{{{RecN}_{L}(i)}{{RecN}_{L}(i)}}}} - \left( {\sum\limits_{i = 0}^{I - 1}{{RecN}_{L}(i)}} \right)^{2}} = \frac{A_{1}}{A_{2}}}} & (3) \\{\beta = \frac{{\sum\limits_{i = 0}^{I - 1}{{RecN}_{C}(i)}} - {\alpha {\sum\limits_{i = 0}^{I - 1}{{RecN}_{L}(i)}}}}{I}} & (4)\end{matrix}$

where RecN_(C)(i) and RecN_(L)(i) are, respectively, the neighboringreconstructed chroma samples and the neighboring down sampledreconstructed luma samples and I is the total number of samples of theneighboring data. For a target N×N chroma block, when both left and topcausal samples are available, the total number of involved samples is2N. When only the left or top causal samples are available, the totalnumber of involved samples is N.

Embodiments of the invention provide for simplification of the abovedescribed luma-based chroma intra-prediction and/or modifications tofacilitate parallel processing. In some embodiments, computationalcomplexity is reduced by sub-sampling RecN_(C)(i) and RecN_(L)(i) beforeperforming the ordinary least squares (OLS) computation. In someembodiments, to facilitate parallel processing, the computation of theparameters α and β is modified to use predicted left chroma and lumasamples instead of the reconstructed left chroma and luma samples. Insome embodiments, to facilitate parallel processing, the reconstructedleft chroma and luma samples are not used, even if available. In someembodiments, the precision for computing the parameter α is reduced by anorm operation without loss of compression efficiency.

FIG. 2 shows a block diagram of a digital system that includes a sourcedigital system 200 that transmits encoded video sequences to adestination digital system 202 via a communication channel 216. Thesource digital system 200 includes a video capture component 204, avideo encoder component 206, and a transmitter component 208. The videocapture component 204 is configured to provide a video sequence to beencoded by the video encoder component 206. The video capture component204 may be, for example, a video camera, a video archive, or a videofeed from a video content provider. In some embodiments, the videocapture component 204 may generate computer graphics as the videosequence, or a combination of live video, archived video, and/orcomputer-generated video.

The video encoder component 206 receives a video sequence from the videocapture component 204 and encodes it for transmission by the transmittercomponent 208. The video encoder component 206 receives the videosequence from the video capture component 204 as a sequence of pictures,divides the pictures into largest coding units (LCUs), and encodes thevideo data in the LCUs. The video encoder component 206 may beconfigured to apply luma-based chroma intra-prediction techniques duringthe encoding process as described herein. An embodiment of the videoencoder component 206 is described in more detail herein in reference toFIG. 3.

The transmitter component 208 transmits the encoded video data to thedestination digital system 202 via the communication channel 216. Thecommunication channel 216 may be any communication medium, orcombination of communication media suitable for transmission of theencoded video sequence, such as, for example, wired or wirelesscommunication media, a local area network, or a wide area network.

The destination digital system 202 includes a receiver component 210, avideo decoder component 212 and a display component 214. The receivercomponent 210 receives the encoded video data from the source digitalsystem 200 via the communication channel 216 and provides the encodedvideo data to the video decoder component 212 for decoding. The videodecoder component 212 reverses the encoding process performed by thevideo encoder component 206 to reconstruct the LCUs of the videosequence. The video decoder component 212 may be configured to applyluma-based chroma intra-prediction techniques during the decodingprocess as described herein. An embodiment of the video decodercomponent 212 is described in more detail below in reference to FIG. 4.

The reconstructed video sequence is displayed on the display component214. The display component 214 may be any suitable display device suchas, for example, a plasma display, a liquid crystal display (LCD), alight emitting diode (LED) display, etc.

In some embodiments, the source digital system 200 may also include areceiver component and a video decoder component and/or the destinationdigital system 202 may include a transmitter component and a videoencoder component for transmission of video sequences both directionsfor video steaming, video broadcasting, and video telephony. Further,the video encoder component 206 and the video decoder component 212 mayperform encoding and decoding in accordance with one or more videocompression standards. The video encoder component 206 and the videodecoder component 212 may be implemented in any suitable combination ofsoftware, firmware, and hardware, such as, for example, one or moredigital signal processors (DSPs), microprocessors, discrete logic,application specific integrated circuits (ASICs), field-programmablegate arrays (FPGAs), etc.

FIG. 3 shows a block diagram of the LCU processing portion of an examplevideo encoder. A coding control component (not shown) sequences thevarious operations of the LCU processing, i.e., the coding controlcomponent runs the main control loop for video encoding. The codingcontrol component receives a digital video sequence and performs anyprocessing on the input video sequence that is to be done at the picturelevel, such as determining the coding type (I, P, or B) of a picturebased on the high level coding structure, e.g., IPPP, IBBP,hierarchical-B, and dividing a picture into LCUs for further processing.The coding control component also may determine the initial LCU CUstructure for each CU and provides information regarding this initialLCU CU structure to the various components of the video encoder asneeded. The coding control component also may determine the initial PUand TU structure for each CU and provides information regarding thisinitial structure to the various components of the video encoder asneeded.

In addition, for pipelined architectures in which multiple PUs and CUsmay be processed concurrently in different components of the LCUprocessing, the coding control component controls the processing of PUsand CUs by various components of the LCU processing in a pipelinefashion. For example, in many embedded systems supporting videoprocessing, there may be one master processor and one or more slaveprocessing modules, e.g., hardware accelerators. The master processoroperates as the coding control component and runs the main control loopfor video encoding, and the slave processing modules are employed to offload certain compute-intensive tasks of video encoding such as motionestimation, motion compensation, intra prediction mode estimation,transformation and quantization, entropy coding, and loop filtering. Theslave processing modules are controlled in a pipeline fashion by themaster processor such that the slave processing modules operate ondifferent blocks of a picture at any given time. That is, the slaveprocessing modules are executed in parallel, each processing itsrespective block while data movement from one processor to another isserial.

The LCU processing receives LCUs of the input video sequence from thecoding control component and encodes the LCUs under the control of thecoding control component to generate the compressed video stream. TheCUs in the CU structure of an LCU may be processed by the LCU processingin a depth-first Z-scan order. The LCUs 300 from the coding control unitare provided as one input of a motion estimation component 320, as oneinput of an intra-prediction component 324, and to a positive input of acombiner 302 (e.g., adder or subtractor or the like). Further, althoughnot specifically shown, the prediction mode of each picture as selectedby the coding control component is provided to a mode selector componentand the entropy encoder 334.

The storage component 318 provides reference data to the motionestimation component 320 and to the motion compensation component 322.The reference data may include one or more previously encoded anddecoded CUs, i.e., reconstructed CUs.

The motion estimation component 320 provides motion data information tothe motion compensation component 322 and the entropy encoder 334. Morespecifically, the motion estimation component 320 performs tests on CUsin an LCU based on multiple inter-prediction modes (e.g., skip mode,merge mode, and normal or direct inter-prediction) and transform blocksizes using reference picture data from storage 318 to choose the bestmotion vector(s)/prediction mode based on a rate distortion coding cost.To perform the tests, the motion estimation component 320 may begin withthe CU structure provided by the coding control component. The motionestimation component 320 may divide each CU indicated in the CUstructure into PUs according to the unit sizes of prediction modes andinto transform units according to the transform block sizes andcalculate the coding costs for each prediction mode and transform blocksize for each CU. The motion estimation component 320 may also computeCU structure for the LCU and PU/TU partitioning structure for a CU ofthe LCU by itself.

For coding efficiency, the motion estimation component 320 may alsodecide to alter the CU structure by further partitioning one or more ofthe CUs in the CU structure. That is, when choosing the best motionvectors/prediction modes, in addition to testing with the initial CUstructure, the motion estimation component 320 may also choose to dividethe larger CUs in the initial CU structure into smaller CUs (within thelimits of the recursive quadtree structure), and calculate coding costsat lower levels in the coding hierarchy. If the motion estimationcomponent 320 changes the initial CU structure, the modified CUstructure is communicated to other components that need the information.

The motion estimation component 320 provides the selected motion vector(MV) or vectors and the selected prediction mode for eachinter-predicted PU of a CU to the motion compensation component 322 andthe selected motion vector (MV), reference picture index (indices),prediction direction (if any) to the entropy encoder 334

The motion compensation component 322 provides motion compensatedinter-prediction information to the mode decision component 326 thatincludes motion compensated inter-predicted PUs, the selectedinter-prediction modes for the inter-predicted PUs, and correspondingtransform block sizes. The coding costs of the inter-predicted PUs arealso provided to the mode decision component 326.

The intra-prediction component 324 provides intra-prediction informationto the mode decision component 326 that includes intra-predicted PUs andthe corresponding intra-prediction modes. That is, the intra-predictioncomponent 324 performs intra-prediction in which tests based on multipleintra-prediction modes and transform unit sizes are performed on CUs inan LCU using previously encoded neighboring PUs from the buffer 328 tochoose the best intra-prediction mode for each PU in the CU based on acoding cost. As is well known, a block of video data may include bothluma data and chroma data, which may be encoded separately. Forsimplicity of explanation, a 4:2:0 sampling rate is assumed in which foreach 2×2 luma sample, there are two corresponding chroma samples. Othersampling rates, e.g., 4:2:2 and 4:4:4, may also be used in embodiments.Further, different intra-prediction modes may be used for luma andchroma in a PU. One of the intra-prediction modes considered by theintra-prediction component 324 for chroma is a luma-based chromaintra-prediction mode, also referred to as a linear method mode (LMmode). The luma-based chroma intra-prediction may be performed accordingto methods described herein.

To perform the tests, the intra-prediction component 324 may begin withthe CU structure provided by the coding control. The intra-predictioncomponent 324 may divide each CU indicated in the CU structure into PUsaccording to the unit sizes of the intra-prediction modes and intotransform units according to the transform block sizes and calculate thecoding costs for each prediction mode and transform block size for eachPU. For coding efficiency, the intra-prediction component 324 may alsodecide to alter the CU structure by further partitioning one or more ofthe CUs in the CU structure. That is, when choosing the best predictionmodes, in addition to testing with the initial CU structure, theintra-prediction component 324 may also chose to divide the larger CUsin the initial CU structure into smaller CUs (within the limits of therecursive quadtree structure), and calculate coding costs at lowerlevels in the coding hierarchy. If the intra-prediction component 324changes the initial CU structure, the modified CU structure iscommunicated to other components that need the information. Further, thecoding costs of the intra-predicted PUs and the associated transformblock sizes are also provided to the mode decision component 326.

The mode decision component 326 selects between the motion-compensatedinter-predicted PUs from the motion compensation component 322 and theintra-predicted PUs from the intra-prediction component 324 based on thecoding costs of the PUs and the picture prediction mode provided by themode selector component. The decision is made at CU level. Based on thedecision as to whether a CU is to be intra- or inter-coded, theintra-predicted PUs or inter-predicted PUs are selected, accordingly.

The output of the mode decision component 326, i.e., the predicted PU,is provided to a negative input of the combiner 302 and to a delaycomponent 330. The associated transform block size is also provided tothe transform component 304. The output of the delay component 330 isprovided to another combiner (i.e., an adder) 338. The combiner 302subtracts the predicted PU from the current PU to provide a residual PUto the transform component 304. The resulting residual PU is a set ofpixel difference values that quantify differences between pixel valuesof the original PU and the predicted PU. The residual blocks of all thePUs of a CU form a residual CU block for the transform component 304.

The transform component 304 performs block transforms on the residual CUto convert the residual pixel values to transform coefficients andprovides the transform coefficients to a quantize component 306. Thetransform component 304 receives the transform block sizes for theresidual CU and applies transforms of the specified sizes to the CU togenerate transform coefficients.

The quantize component 306 quantizes the transform coefficients based onquantization parameters (QPs) and quantization matrices provided by thecoding control component and the transform sizes. The quantizedtransform coefficients are taken out of their scan ordering by a scancomponent 308 and arranged by significance, such as, for example,beginning with the more significant coefficients followed by the lesssignificant.

The ordered quantized transform coefficients for a CU provided via thescan component 308 along with header information for the CU are coded bythe entropy encoder 334, which provides a compressed bit stream to avideo buffer 336 for transmission or storage. The header information mayinclude the prediction mode used for the CU. The entropy encoder 334also encodes the CU and PU structure of each LCU.

The LCU processing includes an embedded decoder. As any compliantdecoder is expected to reconstruct an image from a compressed bitstream, the embedded decoder provides the same utility to the videoencoder. Knowledge of the reconstructed input allows the video encoderto transmit the appropriate residual energy to compose subsequentpictures. To determine the reconstructed input, i.e., reference data,the ordered quantized transform coefficients for a CU provided via thescan component 308 are returned to their original post-transformarrangement by an inverse scan component 310, the output of which isprovided to a dequantize component 312, which outputs a reconstructedversion of the transform result from the transform component 304.

The dequantized transform coefficients are provided to the inversetransform component 314, which outputs estimated residual informationwhich represents a reconstructed version of a residual CU. The inversetransform component 314 receives the transform block size used togenerate the transform coefficients and applies inverse transform(s) ofthe specified size to the transform coefficients to reconstruct theresidual values.

The reconstructed residual CU is provided to the combiner 338. Thecombiner 338 adds the delayed selected CU to the reconstructed residualCU to generate an unfiltered reconstructed CU, which becomes part ofreconstructed picture information. The reconstructed picture informationis provided via a buffer 328 to the intra-prediction component 324 andto an in-loop filter component 316. The in-loop filter component 316applies various filters to the reconstructed picture information toimprove the reference picture used for encoding/decoding of subsequentpictures. The in-loop filter component 316 may, for example, adaptivelyapply low-pass filters to block boundaries according to the boundarystrength to alleviate blocking artifacts causes by the block-based videocoding. The filtered reference data is provided to storage component318.

FIG. 4 shows a block diagram of an example video decoder. The videodecoder operates to reverse the encoding operations, i.e., entropycoding, quantization, transformation, and prediction, performed by thevideo encoder of FIG. 3 to regenerate the pictures of the original videosequence. In view of the above description of a video encoder, one ofordinary skill in the art will understand the functionality ofcomponents of the video decoder without detailed explanation.

The entropy decoding component 400 receives an entropy encoded(compressed) video bit stream and reverses the entropy coding to recoverthe encoded PUs and header information such as the prediction modes andthe encoded CU and PU structures of the LCUs. If the decoded predictionmode is an inter-prediction mode, the entropy decoder 400 thenreconstructs the motion vector(s) as needed and provides the motionvector(s) to the motion compensation component 410.

The inverse quantization component 402 de-quantizes the quantizedtransform coefficients of the residual CU. The inverse transformcomponent 404 transforms the frequency domain data from the inversequantization component 402 back to the residual CU. That is, the inversetransform component 404 applies an inverse unit transform, i.e., theinverse of the unit transform used for encoding, to the de-quantizedresidual coefficients to produce the residual CUs.

A residual CU supplies one input of the addition component 406. Theother input of the addition component 406 comes from the mode switch408. When an inter-prediction mode is signaled in the encoded videostream, the mode switch 408 selects predicted PUs from the motioncompensation component 410 and when an intra-prediction mode issignaled, the mode switch selects predicted PUs from theintra-prediction component 414.

The motion compensation component 410 receives reference data fromstorage 412 and applies the motion compensation computed by the encoderand transmitted in the encoded video bit stream to the reference data togenerate a predicted PU. That is, the motion compensation component 410uses the motion vector(s) from the entropy decoder 400 and the referencedata to generate a predicted PU.

The intra-prediction component 414 receives reference data frompreviously decoded PUs of a current picture from the picture storage 412and applies the intra-prediction computed by the encoder as signaled bythe intra-prediction mode transmitted in the encoded video bit stream tothe reference data to generate a predicted PU. If LM mode is signaled,the intra-prediction component 414 may perform the luma-based chromaintra-prediction according to methods described herein.

The addition component 406 generates a decoded CU by adding thepredicted PUs selected by the mode switch 408 and the residual CU. Theoutput of the addition component 406 supplies the input of the in-loopfilter component 416. The in-loop filter component 416 performs the samefiltering as the encoder. The output of the in-loop filter component 416is the decoded pictures of the video bit stream. Further, the output ofthe in-loop filter component 416 is stored in storage 412 to be used asreference data.

Methods for simplification of luma-based chroma intra-prediction are nowdescribed. Unless otherwise stated, these methods may be used in both anencoder and a decoder.

As shown in FIG. 5, in the prior art, I reconstructed neighboringsamples of the chroma block and I reconstructed and down sampledneighboring samples of the reconstructed luma block are used to derivethe parameters α and β used to compute the predicted chroma samples.These parameters are derived using the OLS technique. As shown in FIG.6, the number of operations required to compute α and β may be reducedby down sampling 600, 602 the reconstructed neighboring luma and chromasamples prior to performing the ordinary least squares computation 604.For example, for an 8×8 block, the reconstructed samples may be downsampled by 2, thus reducing the number of multiplications needed for thecomputation of α and β from 32 to 16. In another example, for a 16×16block, the reconstructed samples may be down sampled by 4, thus reducingthe number of multiplications needed for the computation of α and β from64 to 16. In some embodiments, for improved quality, a smoothing filter606, 608 is applied to the reconstructed neighboring samples prior tothe down sampling 600, 602. Any suitable filter may be used, e.g., [0.5,0.5], [0.25, 0.5, 0.25], etc. Experiments have shown that the downsampling of the reconstructed samples may result in no loss in codingquality.

As shown in FIG. 7, in the prior art, N reconstructed left neighboringsamples and N reconstructed top neighboring samples of the chroma blockand N down sampled reconstructed left neighboring samples and N downsampled reconstructed top neighboring samples of the luma block are usedto derive the parameters α and β used to compute the predicted chromasamples. These parameters are derived using the OLS technique. Inreal-time pipelined systems in which motion estimation, intra predictionestimation, transform/quantization, entropy coding, etc. may be executedon different processing units, the left reconstructed neighboring lumaand chroma samples may not be available in the encoder at the time themode decision is made.

To facilitate use of the LM intra-prediction mode on such systems, thecalculation of the parameters α and β is modified as shown in FIG. 8.Rather than using the reconstructed left neighboring chroma and lumasamples, predicted left neighboring chroma samples, i.e., Pred_(C,left)(0), . . . , Pred_(C,left)(N−1), and predicted left neighboring lumasamples, i.e., Pred_(L,left)′(0), . . . , Pred_(L,left)′(N−1), are usedto derive the parameters. In some embodiments, the parameters α and βmay be computed using only the reconstructed top neighboring chroma andluma samples.

In the prior art, the value of the parameter α is computed at 16-bitprecision. Thus, the multiplication by α in Eq. 1, which is performedfor each chroma sample, requires a 16-bit multiplier. As is illustratedin FIG. 9, the value of α may be normalized 902 after the OLScomputation 900 to reduce the precision of α. The normalization 902 maybe performed, for example, by counting the leading number of zeroes (forpositive numbers) or ones (for negative numbers) and shifting by thecount to normalize the value. In one embodiment, the value of a isnormalized as per the following equation:

a=a3>>Max(0,Log 2(abs(a3))−6)

where a3 is the original value of α and a is the value of a afternormalization. The above equation may be implemented as per thefollowing pseudo code:

Short n=CountLeadingZerosOnes(a);

a=a>>(9−n);

Note that the above equation and pseudo code reduce the precision of αto 7 bits. Other normalization of α may also be used to reduce theprecision of α to, for example, 6 bits or 8 bits. Experiments have shownthat normalization of α to reduce the precision of α to 6, 7, or 8 bitsmay result in no loss of compression efficiency. Further, while FIG. 9shows the input to the OLS 900 being predicted left neighboring chromaand luma samples and reconstructed top neighboring chroma and lumasamples, the normalization of α may also be used when the input to theOLS is reconstructed top neighboring chroma and luma samples only, orwhen the input is reconstructed top and left neighboring chroma and lumasamples.

FIG. 10 shows a method for LM intra-prediction in which three types ofLM intra-prediction are supported: using both the reconstructed top andleft neighboring luma and chroma samples to calculate the parameters αand β, using reconstructed top neighboring luma and chroma samples andpredicted left neighboring luma and chroma samples to calculate theparameters α and β, and using only the reconstructed top neighboringluma and chroma samples to calculate the parameters α and β (even if thereconstructed left neighboring luma and chroma samples are available).The selection of which type of LM intra-prediction type to use is madeon the encoder side and may be signaled to the decoder in a sequenceparameter set, a picture parameter set, and/or at the slice level. Forsimplicity of explanation, 0, 1, and 2 are used to designate specifictypes of LM intra-prediction in the method. Any suitable uniquedesignation of each type may be used.

As shown in FIG. 10, initially the LM mode intra-prediction type isdetermined 1000. In the encoder, the type may be determined in anysuitable way by coding control. In the decoder, the type used by theencoder is decoded from the encoded bit stream. If the type is 0 1004,reconstructed left and top neighboring chroma samples and reconstructedleft and top neighboring luma samples are received. The reconstructedneighboring luma samples may be down sampled to reduce the sampling rateto that of the chroma samples. If the type is 1 1006, predicted leftneighboring luma and chroma samples and reconstructed top neighboringluma and chroma samples are received. The neighboring luma samples maybe down sampled to reduce the sampling rate to that of the chromasamples. If the type is 2 1002, reconstructed top neighboring chroma andluma samples are received. The reconstructed top neighboring lumasamples may be down sampled to reduce the sampling rate to that of thechroma samples.

In the decoder of FIG. 4, the reconstructed samples may be receivedfrom, for example, picture storage 412 or line buffers storing thesamples. The predicted left neighboring samples may be stored afterprocessing of the left neighboring luma and chroma blocks by theintra-prediction component 414 and received from that storage. In theencoder of FIG. 3, the reconstructed samples may be received from, forexample, storage 318 or line buffers storing the samples. The predictedleft neighboring samples may be stored after processing of the leftneighboring luma and chroma blocks by the intra-prediction component 324and received from that storage.

Referring back to FIG. 10, the received neighboring samples are thenfiltered 1008. Any suitable filters may be used and the filters for topneighboring samples and left neighboring samples may be different, e.g.,[0.5, 0.5], [0.25, 0.5, 0.25] etc. Different filters may also be usedfor chroma and luma samples.

The filtered neighboring samples are then down sampled to reduce thenumber of operations needed to compute the parameters α and β. Such downsampling is previously discussed herein. The parameters α and β are thencomputed 1012 by linear regression using the down sampled filteredneighboring samples. Any suitable technique for linear regression may beused. In some embodiments, the ordinary least squares technique aspreviously described is used.

The parameter α is then normalized 1014, and the two parameters are usedto compute 1016 the predicted chroma block from the corresponding downsampled reconstructed luma block as per Eq. 1. Normalization of theparameter α is previously discussed herein.

FIG. 11 shows a method for LM intra-prediction. The interior pixels ofthe reconstructed luma block 1100 are filtered and down sampled togenerate a filtered, down sampled luma block 1102 for generating thepredicted chroma block. The reconstructed top neighboring pixels and thereconstructed left neighboring pixels of the reconstructed luma block1100 are also filtered and down sampled for use in deriving theparameters α and β. The parameters are then derived using thereconstructed top and left neighboring pixels of the correspondingchroma block 1104 and the filtered, down sampled reconstructed top andleft neighboring pixels of the luma block 1100 as per Eq. 3 and 4. Thedivision operations may be approximated using a look-up table (LUT).

Although not specifically shown, the parameter α may be normalized toreduce the precision of the parameter. Normalization of a is previouslydescribed herein. The parameters α and β are then used to compute thepredicted chroma values 1106 from the filtered, down sampled luma block1102 as per Eq. 1.

FIG. 12 is a block diagram of an example digital system suitable for useas an embedded system that may be configured to perform luma basedchroma intra-prediction as described herein during encoding of a videostream and for decoding of such an encoded video stream. This examplesystem-on-a-chip (SoC) is representative of one of a family of DaVinci™Digital Media Processors, available from Texas Instruments, Inc. ThisSoC is described in more detail in “TMS320DM6467 Digital MediaSystem-on-Chip”, SPRS403G, December 2007 or later, which is incorporatedby reference herein.

The SoC 1200 is a programmable platform designed to meet the processingneeds of applications such as video encode/decode/transcode/transrate,video surveillance, video conferencing, set-top box, medical imaging,media server, gaming, digital signage, etc. The SoC 1200 providessupport for multiple operating systems, multiple user interfaces, andhigh processing performance through the flexibility of a fullyintegrated mixed processor solution. The device combines multipleprocessing cores with shared memory for programmable video and audioprocessing with a highly-integrated peripheral set on common integratedsubstrate.

The dual-core architecture of the SoC 1200 provides benefits of both DSPand Reduced Instruction Set Computer (RISC) technologies, incorporatinga DSP core and an ARM926EJ-S core. The ARM926EJ-S is a 32-bit RISCprocessor core that performs 32-bit or 16-bit instructions and processes32-bit, 16-bit, or 8-bit data. The DSP core is a TMS320C64×+TM core witha very-long-instruction-word (VLIW) architecture. In general, the ARM isresponsible for configuration and control of the SoC 1200, including theDSP Subsystem, the video data conversion engine (VDCE), and a majorityof the peripherals and external memories. The switched central resource(SCR) is an interconnect system that provides low-latency connectivitybetween master peripherals and slave peripherals. The SCR is thedecoding, routing, and arbitration logic that enables the connectionbetween multiple masters and slaves that are connected to it.

The SoC 1200 also includes application-specific hardware logic, on-chipmemory, and additional on-chip peripherals. The peripheral set includes:a configurable video port (Video Port I/F), an Ethernet MAC (EMAC) witha Management Data Input/Output (MDIO) module, a 4-bit transfer/4-bitreceive VLYNQ interface, an inter-integrated circuit (I2C) businterface, multichannel audio serial ports (McASP), general-purposetimers, a watchdog timer, a configurable host port interface (HPI);general-purpose input/output (GPIO) with programmable interrupt/eventgeneration modes, multiplexed with other peripherals, UART interfaceswith modem interface signals, pulse width modulators (PWM), an ATAinterface, a peripheral component interface (PCI), and external memoryinterfaces (EMIFA, DDR2). The video port OF is a receiver andtransmitter of video data with two input channels and two outputchannels that may be configured for standard definition television(SDTV) video data, high definition television (HDTV) video data, and rawvideo data capture.

As shown in FIG. 12, the SoC 1200 includes two high-definitionvideo/imaging coprocessors (HDVICP) and a video data conversion engine(VDCE) to offload many video and image processing tasks from the DSPcore. The VDCE supports video frame resizing, anti-aliasing, chrominancesignal format conversion, edge padding, color blending, etc. The HDVICPcoprocessors are designed to perform computational operations requiredfor video encoding such as motion estimation, motion compensation, modedecision, transformation, and quantization. Further, the distinctcircuitry in the HDVICP coprocessors that may be used for specificcomputation operations is designed to operate in a pipeline fashionunder the control of the ARM subsystem and/or the DSP subsystem.

As was previously mentioned, the SoC 1200 may be configured to performluma-based chroma intra-prediction as described herein for encoding abit stream and for decoding a bit stream encoded using luma-based chromaintra-prediction as described herein. For example, the coding control ofthe video encoder of FIG. 8 may be executed on the DSP subsystem or theARM subsystem and at least some of the computational operations of theblock processing, including intra-prediction, motion estimation, entropyencoding, and entropy decoding may be executed on the HDVICPcoprocessors. Intra-prediction on the HDVICP coprocessors may implementtechniques for luma-based chroma intra-prediction as described herein.

OTHER EMBODIMENTS

While the invention has been described with respect to a limited numberof embodiments, those skilled in the art, having benefit of thisdisclosure, will appreciate that other embodiments can be devised whichdo not depart from the scope of the invention as disclosed herein.

For example, previously described embodiments assumed a 4:2:0 samplingrate. Other sampling rates may also be used, such as 4:2:2 and 4:4:4, aslong as the number of neighboring samples I is a power of 2. For a 4:4:4sampling rate, the initial down sampling of the luma block to the chromasampling rate is not needed. For a 4:2:2 sampling rate, the initial downsampling of the luma block could be different in the horizontal andvertical directions. For example, for a 16×16 luma block, the chromablock would be 16×8 and the luma block would need to be down sampleddifferently in the horizontal and vertical directions.

In some embodiments, if neighboring samples are not available, thevalues of available samples are substituted for the unavailable samples.Any suitable available samples values may be used. Neighboring samplesmay not be available, for example, at slice boundaries, or whenconstrained intra-prediction (CIP) is used. When CIP is used, a PU in aninter-predicted picture cannot be intra-predicted using information fromneighboring inter-predicted PUs in the picture.

Embodiments of the methods, encoders, and decoders described herein maybe implemented in hardware, software, firmware, or any combinationthereof. If completely or partially implemented in software, thesoftware may be executed in one or more processors, such as amicroprocessor, application specific integrated circuit (ASIC), fieldprogrammable gate array (FPGA), or digital signal processor (DSP). Thesoftware instructions may be initially stored in a computer-readablemedium and loaded and executed in the processor. In some cases, thesoftware instructions may also be sold in a computer program product,which includes the computer-readable medium and packaging materials forthe computer-readable medium. In some cases, the software instructionsmay be distributed via removable computer readable media, via atransmission path from computer readable media on another digitalsystem, etc. Examples of computer-readable media include non-writablestorage media such as read-only memory devices, writable storage mediasuch as disks, flash memory, memory, or a combination thereof.

It is therefore contemplated that the appended claims will cover anysuch modifications of the embodiments as fall within the true scope ofthe invention.

1. A method for luma-based chroma intra-prediction in a video encoder ora video decoder, the method comprising: filtering reconstructedneighboring samples of a reconstructed down sampled luma block;computing parameters α and β of a linear model using the filtered,reconstructed neighboring samples of the reconstructed down sampled lumablock and reconstructed neighboring samples of a corresponding chromablock, wherein the linear model is Pred_(C)[x,y]=α·Rec_(L)′[x,y]+,wherein x and y are sample coordinates, Pred_(C) is predicted chromasamples, and Rec_(L)′ is samples of the reconstructed down sampled lumablock; and computing samples of a predicted chroma block fromcorresponding samples of the reconstructed down sampled luma block usingthe linear model and the parameters.
 2. The method of claim 1, furthercomprising: filtering the reconstructed neighboring samples of thecorresponding chroma block prior to computing parameters α and β, andwherein computing parameters α and β comprises computing the parametersusing the filtered, reconstructed neighboring samples of thereconstructed down sampled luma block and the filtered, reconstructedneighboring samples of the corresponding chroma block.
 3. The method ofclaim 1, further comprising: normalizing the parameter α prior tocomputing samples of the predicted chroma block.
 4. The method of claim3, wherein normalizing the parameter α comprises reducing precision of αto one selected from a group consisting of 6 bits, 7 bits, and 8 bits.5. The method of claim 1, further comprising: down sampling thereconstructed filtered neighboring samples of the reconstructed downsampled luma block and the reconstructed neighboring samples of thecorresponding chroma block prior to computing parameters α and β; andwherein computing parameters α and β comprises computing the parametersusing the down sampled reconstructed filtered neighboring samples of thereconstructed down sampled luma block and the down sampled reconstructedneighboring samples of the corresponding chroma block.
 6. The method ofclaim 1, wherein the reconstructed neighboring samples of thecorresponding chroma block consist of reconstructed top neighboringsamples and reconstructed left neighboring samples of the correspondingchroma block, and the reconstructed neighboring samples of thereconstructed down sampled luma block consist of reconstructed topneighboring samples and reconstructed left neighboring samples of thereconstructed down sampled luma block.
 7. The method of claim 1, whereinthe reconstructed neighboring samples of the corresponding chroma blockconsist of reconstructed top neighboring samples of the correspondingchroma block and the reconstructed neighboring samples of thereconstructed down sampled luma block consist of reconstructed topneighboring samples of the reconstructed down sampled luma block.
 8. Themethod of claim 1, further comprising: receiving predicted leftneighboring samples of the corresponding chroma block and of thereconstructed down sampled luma block; and wherein computing parametersα and β comprises computing the parameters using the predicted leftneighboring samples of the corresponding chroma block and of thereconstructed down sampled luma block, the filtered, reconstructedneighboring samples of the reconstructed down sampled luma block, andthe reconstructed neighboring samples of the corresponding chroma block,wherein the reconstructed neighboring samples of the reconstructed downsampled luma block consist of reconstructed top neighboring samples ofthe reconstructed down sampled luma block, and the reconstructedneighboring samples of the corresponding chroma block consist ofreconstructed top neighboring samples of the corresponding chroma block.9. A method for luma-based chroma intra-prediction in a video encoder ora video decoder, the method comprising: computing parameters α and β ofa linear model using reconstructed neighboring samples of areconstructed down sampled luma block and of a corresponding chromablock, wherein the linear model is Pred_(C)[x,y]=α·Rec_(L)′[x,y]+,wherein x and y are sample coordinates, Pred_(C) is predicted chromasamples, and Rec_(L)′ is samples of the reconstructed down sampled lumablock; normalizing the parameter α; and computing samples of a predictedchroma block from corresponding samples of the reconstructed downsampled luma block using the linear model and the parameters.
 10. Themethod of claim 9, further comprising: filtering the reconstructedneighboring samples of the reconstructed down sampled luma block priorto computing parameters α and β, wherein the parameters are computedusing the filtered reconstructed neighboring samples of thereconstructed down sampled luma block and the reconstructed neighboringsamples of the corresponding chroma block.
 11. The method of claim 9,wherein normalizing the parameter α comprises reducing precision of α toone selected from a group consisting of 6 bits, 7 bits, and 8 bits. 12.The method of claim 9, further comprising: down sampling thereconstructed neighboring samples of the reconstructed down sampled lumablock and the corresponding chroma block prior to computing parameters αand β, wherein the parameters are computed using the down sampledreconstructed neighboring samples of the reconstructed down sampled lumablock and the corresponding chroma block.
 13. The method of claim 9,wherein the reconstructed neighboring samples of the correspondingchroma block consist of reconstructed top neighboring samples andreconstructed left neighboring samples of the corresponding chromablock, and the reconstructed neighboring sample of the reconstructeddown sampled luma block consist of reconstructed top neighboring samplesand reconstructed left neighboring samples of the reconstructed downsampled luma block.
 14. The method of claim 9, wherein the reconstructedneighboring samples of the corresponding chroma block consist ofreconstructed top neighboring samples of the corresponding chroma blockand the reconstructed neighboring samples of the reconstructed downsampled luma block consist of reconstructed top neighboring samples ofthe reconstructed down sampled luma block.
 15. The method of claim 9,further comprising: receiving predicted left neighboring samples of thecorresponding chroma block and of the reconstructed down sampled lumablock; and wherein computing parameters α and β comprises computing theparameters using the predicted left neighboring samples of thecorresponding chroma block and of the reconstructed down sampled lumablock, the filtered, reconstructed neighboring samples of thereconstructed down sampled luma block, and the reconstructed neighboringsamples of the corresponding chroma block, wherein the reconstructedneighboring samples of the reconstructed down sampled luma block consistof reconstructed top neighboring samples of the reconstructed downsampled luma block, and the reconstructed neighboring samples of thecorresponding chroma block consist of reconstructed top neighboringsamples of the corresponding chroma block.
 16. A method for luma-basedchroma intra-prediction in a video encoder or a video decoder, themethod comprising: determining a type of luma-based chromaintra-prediction to be used, wherein the type is one of a plurality oftypes of luma-based chroma intra-prediction; and performing luma-basedchroma intra-prediction according to the determined type to generate apredicted chroma block.
 17. The method of claim 16, wherein performingluma-based chroma intra-prediction comprises: computing parameters α andβ of a linear model using neighboring samples of a reconstructed downsampled luma block and of a corresponding chroma block, wherein thelinear model is Pred_(C)[x,y]=α·Rec_(L)′[x,y]+, wherein x and y aresample coordinates, Pred_(C) is predicted chroma samples, and Rec_(L)′is samples of the reconstructed down sampled luma block; and computingsamples of a predicted chroma block from corresponding samples of thereconstructed down sampled luma block using the linear model and theparameters.
 18. The method of claim 17, wherein for a first type ofluma-based chroma intra-prediction, the neighboring samples consist ofreconstructed top neighboring samples and reconstructed left neighboringsamples of the corresponding chroma block, reconstructed top neighboringsamples and reconstructed left neighboring samples of the reconstructeddown sampled luma block, for a second type of luma-based chromaintra-prediction, the neighboring samples consist of reconstructed topneighboring samples of the corresponding chroma block and reconstructedtop neighboring samples of the reconstructed down sampled luma block,and for a third type of luma-based chroma intra-prediction, theneighboring samples consist of reconstructed top neighboring samples ofthe corresponding chroma block, reconstructed top neighboring samples ofthe reconstructed down sampled luma block, predicted left neighboringsamples of the corresponding chroma block, and predicted leftneighboring samples of the reconstructed down sampled luma block. 19.The method of claim 17, further comprising: filtering the neighboringsamples prior to computing parameters α and β.
 20. The method of claim17, further comprising: normalizing the parameter α prior to computingsamples of the predicted chroma block.